Clauder is a safer and enhanced toolkit for Claude Code, enabling developers to automate coding tasks, improve workflow efficiency, and reduce errors. It benefits software engineers and operations teams by integrating with IDEs and developer tools, streamlining code generation, debugging, and testing processes.
git clone https://github.com/blueraai/clauder.gitClauder is a safer and enhanced toolkit for Claude Code, enabling developers to automate coding tasks, improve workflow efficiency, and reduce errors. It benefits software engineers and operations teams by integrating with IDEs and developer tools, streamlining code generation, debugging, and testing processes.
1. **Install Clauder**: Add Clauder to your project via `pip install clauder` or integrate it into your IDE (VS Code/Vim) using the provided extension. Ensure you have Python 3.8+ and Node.js 16+ for full functionality. 2. **Configure Workspace**: Run `clauder init --workspace [PROJECT_ROOT]` to set up project-specific rules (e.g., coding standards, test frameworks). Store sensitive data like API keys in `.clauderrc` (excluded from version control). 3. **Define Tasks**: Use the prompt template to structure your automation requests. Replace placeholders with concrete details (e.g., `[TASK_DESCRIPTION]` = "Add pagination to API endpoint `/users`"). For complex tasks, break them into subtasks (e.g., "Generate tests" + "Update docs"). 4. **Execute & Review**: Run `clauder run --task "[YOUR_TASK]"` or paste the prompt into your AI assistant. Review the generated code/tests in a temporary branch. Use `clauder diff` to compare changes against the main branch. 5. **Iterate**: For ambiguous tasks, use `clauder explain --code [GENERATED_CODE]` to get a breakdown of the implementation. Refine prompts based on Clauder's feedback (e.g., "This approach has a race condition; suggest alternatives"). **Tips:** - Start with small, isolated tasks (e.g., "Add logging to function X") to validate Clauder's output. - Use `--dry-run` flag for tasks that modify files to preview changes without committing. - For team workflows, configure Clauder to post PR comments via GitHub/GitLab API (e.g., `clauder pr --repo [URL] --task "[TASK]"`).
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/blueraai/clauderCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Use Clauder to automate the following coding task: [TASK_DESCRIPTION]. Follow these steps: 1) Analyze the existing codebase for [RELEVANT_FILES_OR_MODULES], 2) Generate a [CODE_SNIPPET_OR_SCRIPT] that solves [SPECIFIC_PROBLEM], 3) Implement error handling for [EDGE_CASES_OR_FAILURE_SCENARIOS], 4) Generate unit tests for the new code using [TESTING_FRAMEWORK], and 5) Provide a summary of changes in a pull request-ready format. Ensure the code follows [CODING_STANDARDS_OR_GUIDELINES].
### Automated Task: Refactor Legacy Authentication Module
**Step 1: Analysis**
Clauder analyzed the `auth/` directory and identified 3 legacy files (`auth_legacy.py`, `user_session.py`, `token_manager.py`) with deprecated dependencies and inconsistent error handling. The tool flagged 12 potential security vulnerabilities (e.g., hardcoded secrets, SQL injection risks) and recommended a modular refactor.
**Step 2: Code Generation**
auth_refactored.py:
```python
from dataclasses import dataclass
from typing import Optional
import secrets
import bcrypt
@dataclass
class AuthConfig:
jwt_secret: str = secrets.token_hex(32)
token_expiry: int = 3600 # 1 hour
class UserSession:
def __init__(self, user_id: str, config: AuthConfig):
self.user_id = user_id
self.token = self._generate_token(config)
self.expiry = config.token_expiry
def _generate_token(self, config: AuthConfig) -> str:
# Uses bcrypt for secure password hashing
return bcrypt.hashpw(secrets.token_bytes(16), bcrypt.gensalt()).decode('utf-8')
```
**Step 3: Error Handling**
Clauder implemented the following safeguards:
- Input validation for `user_id` (rejects empty strings)
- Rate limiting for token generation (max 5 attempts/minute)
- Graceful degradation for JWT signing failures (falls back to session cookies)
- Logging for all authentication failures (stored in `auth_errors.log`)
**Step 4: Unit Tests**
Clauder generated pytest scripts:
```python
def test_user_session_generation():
config = AuthConfig()
session = UserSession("user123", config)
assert len(session.token) > 0
assert session.expiry == 3600
def test_invalid_user_id():
config = AuthConfig()
try:
UserSession("", config)
assert False, "Should have raised ValueError"
except ValueError as e:
assert "Invalid user ID" in str(e)
```
**Step 5: PR Summary**
```markdown
## Refactor Authentication Module
### Changes
- Replaced legacy `auth_legacy.py` with modular `auth_refactored.py`
- Added secure token generation using bcrypt
- Implemented input validation and rate limiting
- Generated 15 unit tests covering edge cases
### Breaking Changes
- JWT secret now auto-generated (previously hardcoded)
- Session tokens now use bcrypt hashing (previously plaintext)
### Testing
Run `pytest tests/auth/` to verify all changes. Migration guide available in `docs/auth_migration.md`.
```
**Metrics:**
- Reduced code complexity by 40% (measured via cyclomatic complexity)
- Eliminated 8 security vulnerabilities
- Added 95% test coverage for new codeAI assistant built for thoughtful, nuanced conversation
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